Habit Formation, Price Indexation and Wage Indexation in the DSGE Model: Specification, Estimation and Model Fit

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14560%2F11%3A00052649" target="_blank" >RIV/00216224:14560/11:00052649 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Habit Formation, Price Indexation and Wage Indexation in the DSGE Model: Specification, Estimation and Model Fit

Popis výsledku v původním jazyce

In order to determine which specification provides better fit of the data, this paper presents several specifications of a closed economy DSGE model with nominal rigidities. The goal of this paper is to find out whether some characteristics widely used in New Keynesian DSGE models, such as habit formation in consumption, price indexation and wage indexation, provide better fit of the macroeconomic data. Model specifications are estimated on the data of the US economy and Euro Area 12 economy, using Bayesian techniques, particularly the Metropolis Hastings algorithm. The data fit measure is a Bayes factor calculated from marginal likelihoods. Results suggest that including habit formation in consumption significantly improves the empirical data fit of the model, whereas including partial price indexation and partial wage indexation does not improve the empirical data fit of the model. Variants with full price indexation and full wage indexation were the worst ones concerning their data

Název v anglickém jazyce

Habit Formation, Price Indexation and Wage Indexation in the DSGE Model: Specification, Estimation and Model Fit

Popis výsledku anglicky

In order to determine which specification provides better fit of the data, this paper presents several specifications of a closed economy DSGE model with nominal rigidities. The goal of this paper is to find out whether some characteristics widely used in New Keynesian DSGE models, such as habit formation in consumption, price indexation and wage indexation, provide better fit of the macroeconomic data. Model specifications are estimated on the data of the US economy and Euro Area 12 economy, using Bayesian techniques, particularly the Metropolis Hastings algorithm. The data fit measure is a Bayes factor calculated from marginal likelihoods. Results suggest that including habit formation in consumption significantly improves the empirical data fit of the model, whereas including partial price indexation and partial wage indexation does not improve the empirical data fit of the model. Variants with full price indexation and full wage indexation were the worst ones concerning their data

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

<a href="/cs/project/1M0524" target="_blank" >1M0524: Centrum výzkumu konkurenční schopnosti české ekonomiky</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Národohospodářský obzor ? Review of Economic Perspectives

ISSN

1213-2446

e-ISSN

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Svazek periodika

11

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

23

Strana od-do

71-92

Kód UT WoS článku

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EID výsledku v databázi Scopus

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